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Stage: Query Execution Time Prediction in Amazon Redshift

Summary: Stage is a hierarchical predictor for Redshift, combining a cache, a per-instance light model with uncertainty, and a global transferable model. It mitigates cold starts and workload shifts, delivering ~20% lower latency with practical inference and memory. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h25cd3c28d011c209
Venue
SIGMOD
Year
2024
Pagerank
6.2218868e-05
Overall Rank
5,216 | 64.95%
DOI
10.1145/3626246.3653391
PDF
Download (CC BY 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wu_sigmod24,
        title = {{Stage: Query Execution Time Prediction in Amazon Redshift}},
        author = {Wu, Ziniu and Marcus, Ryan and Liu, Zhengchun and Negi, Parimarjan and Nathan, Vikram and Pfeil, Pascal and Saxena, Gaurav and Rahman, Mohammad and Narayanaswamy, Balakrishnan and Kraska, Tim},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626246.3653391},
        url = {https://dl.acm.org/doi/10.1145/3626246.3653391},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 21 of 21 citing papers.

Rank Citing Paper Year Venue Pagerank
7,464 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5189616e-05
7,869 Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD 2024 VLDB 5.4342182e-05
7,981 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4117272e-05
8,643 PBench: Workload Synthesizer with Real Statistics for Cloud Analytics Benchmarking 2025 VLDB 5.2956539e-05
8,994 Resource-Adaptive Query Execution with Paged Memory Management 2025 CIDR 5.2408882e-05
9,134 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2223611e-05
9,635 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1453041e-05
9,645 QURE: AI-Assisted and Automatically Verified UDF Inlining 2025 SIGMOD 5.1437878e-05
9,962 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1014161e-05
10,152 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.0691578e-05
10,320 veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System 2025 VLDB 5.0362412e-05
10,362 Survivorship Bias in Industrial Database Workloads 2026 CIDR 4.9769913e-05
10,459 EncoderForge: Generating Efficient SQL for Encoders in Machine Learning Inference Pipelines 2026 SIGMOD 4.9769913e-05
10,701 The Case For Language Model Approximated LIKE Predicate 2026 SIGMOD 4.9769913e-05
10,751 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9769913e-05
10,918 Incremental Query Optimizer Statistics in Amazon Redshift 2026 VLDB 4.9769913e-05
10,950 Ultron: History-Based Query Optimization at Databricks 2026 VLDB 4.9769913e-05
11,064 SafeLoad: Efficient Admission Control Framework for Identifying Memory-Overloading Queries in Cloud Data Warehouses 2026 VLDB 4.9769913e-05
11,078 KEN: An Execution Engine for Unstructured Database Systems 2026 VLDB 4.9769913e-05
11,081 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9769913e-05
11,431 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 31 of 31 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046363107
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
123 Schism: a Workload-Driven Approach to Database Replication and Partitioning 2010 VLDB 0.00030749898
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
386 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019446558
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
510 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017059914
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016408613
681 Amazon Redshift Re-invented 2022 SIGMOD 0.0001482366
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014814858
869 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013363241
981 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012713454
1,051 Tiresias: The Database Oracle for How-To Queries 2012 SIGMOD 0.00012274277
1,188 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011598149
1,195 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011574218
1,280 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011224914
1,800 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.6082185e-05
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,139 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 8.9735524e-05
2,837 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.9495917e-05
2,844 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9446987e-05
2,879 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 7.9126862e-05
2,983 WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases 2016 VLDB 7.7831414e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4233639e-05
3,565 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.200937e-05
4,391 Self-Tuning Query Scheduling for Analytical Workloads 2021 SIGMOD 6.6196806e-05
4,568 HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach 2022 SIGMOD 6.5279657e-05
5,062 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.2896995e-05
5,236 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.2153504e-05
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1 5,658 Uncertainty Aware Query Execution Time Prediction 2014 VLDB
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